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Ying Wei 0001
魏 颖
Person information
- unicode name: 魏 颖
- affiliation: Nanyang Technological University, China
- affiliation (former): City University of Hong Kong, Department of Computer Science, Hong Kong
- affiliation (former): Tencent AI Lab, Guangdong, China
Other persons with the same name
- Ying Wei — disambiguation page
- Ying Wei 0002 — State University of New York at Stony Brook, Stony Brook, NY, USA
- Ying Wei 0003
— Department of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing, China
- Ying Wei 0004
- Ying Wei 0005
- Ying Wei 0006 — Xiamen University, Tan Kah Kee College, Xiamen, China
- Ying Wei 0007
- Ying Wei 0008 — Chinese Academy of Sciences, Institute of Software, Beijing, China
- Ying Wei 0009
- Ying Wei 0010
- Ying Wei 0011
- Ying Wei 0012 — Yangzhou University, School of Information Engineering, Yangzhou, China
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2020 – today
- 2024
- [c51]Yemin Yu, Luotian Yuan, Ying Wei, Hanyu Gao, Fei Wu, Zhihua Wang, Xinhai Ye:
RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction. AAAI 2024: 374-382 - [c50]Tianqi Zhong, Zhaoyi Li, Quan Wang, Linqi Song, Ying Wei, Defu Lian, Zhendong Mao:
Benchmarking and Improving Compositional Generalization of Multi-aspect Controllable Text Generation. ACL (1) 2024: 6486-6517 - [c49]Zhaoyi Li, Gangwei Jiang, Hong Xie, Linqi Song, Defu Lian, Ying Wei:
Understanding and Patching Compositional Reasoning in LLMs. ACL (Findings) 2024: 9668-9688 - [c48]Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Surr:
MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-Wise Pruning Error Metric. CVPR 2024: 27360-27370 - [c47]Weichuan Wang, Zhaoyi Li, Defu Lian, Chen Ma, Linqi Song, Ying Wei:
Mitigating the Language Mismatch and Repetition Issues in LLM-based Machine Translation via Model Editing. EMNLP 2024: 15681-15700 - [c46]Yichen Wu, Long-Kai Huang, Renzhen Wang, Deyu Meng, Ying Wei:
Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction. ICLR 2024 - [c45]Luotian Yuan, Yemin Yu, Ying Wei, Yongwei Wang, Zhihua Wang, Fei Wu:
Active Retrosynthetic Planning Aware of Route Quality. ICLR 2024 - [c44]Shengzhuang Chen, Jihoon Tack, Yunqiao Yang, Yee Whye Teh, Jonathan Richard Schwarz, Ying Wei:
Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts. ICML 2024 - [c43]Hongming Piao, Yichen Wu, Dapeng Wu, Ying Wei:
Federated Continual Learning via Prompt-based Dual Knowledge Transfer. ICML 2024 - [c42]Yichen Wu, Hong Wang, Peilin Zhao, Yefeng Zheng, Ying Wei, Long-Kai Huang:
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization. ICML 2024 - [i32]Chang Liao, Yemin Yu, Yu Mei, Ying Wei:
From Words to Molecules: A Survey of Large Language Models in Chemistry. CoRR abs/2402.01439 (2024) - [i31]Zhaoyi Li, Gangwei Jiang, Hong Xie, Linqi Song
Understanding and Patching Compositional Reasoning in LLMs. CoRR abs/2402.14328 (2024) - [i30]Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Sun:
MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-wise Pruning Error Metric. CoRR abs/2403.07839 (2024) - [i29]Shengzhuang Chen, Jihoon Tack, Yunqiao Yang, Yee Whye Teh, Jonathan Richard Schwarz, Ying Wei:
Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts. CoRR abs/2403.08477 (2024) - [i28]Tianqi Zhong, Zhaoyi Li, Quan Wang, Linqi Song, Ying Wei, Defu Lian, Zhendong Mao:
Benchmarking and Improving Compositional Generalization of Multi-aspect Controllable Text Generation. CoRR abs/2404.04232 (2024) - [i27]Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei:
Rotation and Permutation for Advanced Outlier Management and Efficient Quantization of LLMs. CoRR abs/2406.01721 (2024) - [i26]Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei:
Interpretable Catastrophic Forgetting of Large Language Model Fine-tuning via Instruction Vector. CoRR abs/2406.12227 (2024) - [i25]Weichuan Wang, Zhaoyi Li, Defu Lian, Chen Ma, Linqi Song, Ying Wei:
Mitigating the Language Mismatch and Repetition Issues in LLM-based Machine Translation via Model Editing. CoRR abs/2410.07054 (2024) - 2023
- [j3]Chun He, Xinhai Ye
DeepAlgPro: an interpretable deep neural network model for predicting allergenic proteins. Briefings Bioinform. 24(4) (2023) - [c41]Yinjie Jiang, Ying Wei, Fei Wu, Zhengxing Huang, Kun Kuang, Zhihua Wang:
Learning Chemical Rules of Retrosynthesis with Pre-training. AAAI 2023: 5113-5121 - [c40]Zhaoyi Li, Ying Wei, Defu Lian:
Learning to Substitute Spans towards Improving Compositional Generalization. ACL (1) 2023: 2791-2811 - [c39]Qing Guo, Jie Yang, Yufeng Xiao, Huaqing Wang, Mingan Yu, Ying Wei, Zhenlong Zhao:
A Joint Attention Module and Deformable Transformer Network for Hyperparathyroidism Detection. BIBM 2023: 4893-4895 - [c38]Weixia Zhang, Guangtao Zhai, Ying Wei, Xiaokang Yang, Kede Ma
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective. CVPR 2023: 14071-14081 - [c37]Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Zhang, Jun Zhou, Defu Lian, Ying Wei:
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompts. EMNLP (Findings) 2023: 12081-12095 - [c36]Yunqiao Yang
Concept-wise Fine-tuning Matters in Preventing Negative Transfer. ICCV 2023: 18707-18717 - [c35]Shengzhuang Chen, Long-Kai Huang, Jonathan Richard Schwarz, Yilun Du, Ying Wei:
Secure Out-of-Distribution Task Generalization with Energy-Based Models. NeurIPS 2023 - [i24]Weixia Zhang, Guangtao Zhai, Ying Wei, Xiaokang Yang, Kede Ma:
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective. CoRR abs/2303.14968 (2023) - [i23]Zhaoyi Li, Ying Wei, Defu Lian:
Learning to Substitute Spans towards Improving Compositional Generalization. CoRR abs/2306.02840 (2023) - [i22]Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Y. Zhang, Jun Zhou, Defu Lian
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt. CoRR abs/2310.13024 (2023) - [i21]Yunqiao Yang, Long-Kai Huang, Ying Wei:
Concept-wise Fine-tuning Matters in Preventing Negative Transfer. CoRR abs/2311.06868 (2023) - [i20]Yemin Yu, Luotian Yuan, Ying Wei, Hanyu Gao, Xinhai Ye, Zhihua Wang, Fei Wu:
RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction. CoRR abs/2312.10900 (2023) - 2022
- [c34]Juan Zha, Zheng Li, Ying Wei, Yu Zhang:
Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering. EMNLP (Findings) 2022: 5236-5247 - [c33]Long-Kai Huang, Junzhou Huang, Yu Rong, Qiang Yang, Ying Wei:
Frustratingly Easy Transferability Estimation. ICML 2022: 9201-9225 - [c32]Yinjie Jiang, Zhengyu Chen, Kun Kuang, Luotian Yuan, Xinhai Ye, Zhihua Wang, Fei Wu, Ying Wei:
The Role of Deconfounding in Meta-learning. ICML 2022: 10161-10176 - [c31]Gangwei Jiang, Shiyao Wang, Tiezheng Ge, Yuning Jiang, Ying Wei
Self-Supervised Text Erasing with Controllable Image Synthesis. ACM Multimedia 2022: 1973-1983 - [c30]Long-Kai Huang, Ying Wei:
Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization. NeurIPS 2022 - [c29]Yichen Wu, Long-Kai Huang, Ying Wei:
Adversarial Task Up-sampling for Meta-learning. NeurIPS 2022 - [c28]Yemin Yu, Ying Wei, Kun Kuang, Zhengxing Huang, Huaxiu Yao, Fei Wu:
GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy. NeurIPS 2022 - [c27]Qing Guo, Yufeng Xiao, Huaqing Wang, Mingan Yu, Ying Wei, Zhenlong Zhao:
A Benchmark and Transformer-based Approach for Automated Hyperparathyroidism Detection. SMC 2022: 2397-2402 - [i19]Gangwei Jiang, Shiyao Wang, Tiezheng Ge, Yuning Jiang, Ying Wei, Defu Lian
Self-Supervised Text Erasing with Controllable Image Synthesis. CoRR abs/2204.12743 (2022) - [i18]Yichen Wu, Long-Kai Huang, Ying Wei:
Learning to generate imaginary tasks for improving generalization in meta-learning. CoRR abs/2206.04335 (2022) - [i17]Juan Zha, Zheng Li, Ying Wei, Yu Zhang:
Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering. CoRR abs/2211.08588 (2022) - 2021
- [c26]Zheng Li, Danqing Zhang, Tianyu Cao, Ying Wei
MetaTS: Meta Teacher-Student Network for Multilingual Sequence Labeling with Minimal Supervision. EMNLP (1) 2021: 3183-3196 - [c25]Ying Wei, Peilin Zhao, Junzhou Huang:
Meta-learning Hyperparameter Performance Prediction with Neural Processes. ICML 2021: 11058-11067 - [c24]Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li:
Improving Generalization in Meta-learning via Task Augmentation. ICML 2021: 11887-11897 - [c23]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. NeurIPS 2021: 7497-7509 - [c22]Huaxiu Yao, Ying Wei, Long-Kai Huang, Ding Xue, Junzhou Huang, Zhenhui Li:
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery. NeurIPS 2021: 8256-8268 - [i16]Long-Kai Huang, Ying Wei, Yu Rong, Qiang Yang, Junzhou Huang:
Frustratingly Easy Transferability Estimation. CoRR abs/2106.09362 (2021) - [i15]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. CoRR abs/2110.14057 (2021) - 2020
- [j2]Yifan Zhang
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. IEEE Trans. Image Process. 29: 7834-7844 (2020) - [c21]Huaxiu Yao, Chuxu Zhang
Graph Few-Shot Learning via Knowledge Transfer. AAAI 2020: 6656-6663 - [c20]Jiabo Chen, Qing Guo, Zixun Jiang, Huaqing Wang, Mingan Yu, Ying Wei
Recognition of Hyperparathyroidism based on Transfer Learning. BIBM 2020: 2959-2961 - [c19]Zheng Li, Mukul Kumar, William Headden, Bing Yin, Ying Wei
Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages. EMNLP (1) 2020: 2290-2301 - [c18]Kuo Zhong, Ying Wei
TranSlider: Transfer Ensemble Learning from Exploitation to Exploration. KDD 2020: 368-378 - [c17]Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang:
Self-Supervised Graph Transformer on Large-Scale Molecular Data. NeurIPS 2020 - [c16]Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei, Junzhou Huang:
Adversarial Sparse Transformer for Time Series Forecasting. NeurIPS 2020 - [c15]Yinghua Zhang, Yu Zhang, Ying Wei
Fisher Deep Domain Adaptation. SDM 2020: 469-477 - [i14]Yinghua Zhang, Yu Zhang, Ying Wei, Kun Bai, Yangqiu Song, Qiang Yang:
Fisher Deep Domain Adaptation. CoRR abs/2003.05636 (2020) - [i13]Yifan Zhang, Shuaicheng Niu, Zhen Qiu, Ying Wei, Peilin Zhao, Jianhua Yao, Junzhou Huang, Qingyao Wu, Mingkui Tan:
COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19. CoRR abs/2005.01577 (2020) - [i12]Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang:
GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data. CoRR abs/2007.02835 (2020) - [i11]Yifan Zhang, Ying Wei, Qingyao Wu, Peilin Zhao, Shuaicheng Niu, Junzhou Huang, Mingkui Tan:
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. CoRR abs/2007.07222 (2020) - [i10]Huaxiu Yao, Longkai Huang, Ying Wei, Li Tian, Junzhou Huang, Zhenhui Li:
Don't Overlook the Support Set: Towards Improving Generalization in Meta-learning. CoRR abs/2007.13040 (2020)
2010 – 2019
- 2019
- [c14]Zheng Li, Ying Wei
Exploiting Coarse-to-Fine Task Transfer for Aspect-Level Sentiment Classification. AAAI 2019: 4253-4260 - [c13]Zheng Li, Xin Li, Ying Wei
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning. EMNLP/IJCNLP (1) 2019: 4589-4599 - [c12]Huaxiu Yao, Ying Wei, Junzhou Huang, Zhenhui Li:
Hierarchically Structured Meta-learning. ICML 2019: 7045-7054 - [c11]Yifan Zhang, Hanbo Chen, Ying Wei
From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification. MICCAI (1) 2019: 360-368 - [c10]Huaxiu Yao, Yiding Liu, Ying Wei
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction. WWW 2019: 2181-2191 - [i9]Huaxiu Yao, Yiding Liu, Ying Wei, Xianfeng Tang, Zhenhui Li:
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction. CoRR abs/1901.08518 (2019) - [i8]Huaxiu Yao, Ying Wei, Junzhou Huang, Zhenhui Li:
Hierarchically Structured Meta-learning. CoRR abs/1905.05301 (2019) - [i7]Ying Wei, Peilin Zhao, Huaxiu Yao, Junzhou Huang:
Transferable Neural Processes for Hyperparameter Optimization. CoRR abs/1909.03209 (2019) - [i6]Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li:
Graph Few-shot Learning via Knowledge Transfer. CoRR abs/1910.03053 (2019) - [i5]Zheng Li, Xin Li, Ying Wei, Lidong Bing, Yu Zhang, Qiang Yang:
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning. CoRR abs/1910.14192 (2019) - [i4]Yifan Zhang, Ying Wei, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Mingkui Tan, Junzhou Huang:
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. CoRR abs/1911.07293 (2019) - 2018
- [c9]Bo Liu, Ying Wei, Yu Zhang, Zhixian Yan, Qiang Yang:
Transferable Contextual Bandit for Cross-Domain Recommendation. AAAI 2018: 3619-3626 - [c8]Zheng Li, Ying Wei, Yu Zhang, Qiang Yang:
Hierarchical Attention Transfer Network for Cross-Domain Sentiment Classification. AAAI 2018: 5852-5859 - [c7]Ying Wei, Yu Zhang, Junzhou Huang, Qiang Yang:
Transfer Learning via Learning to Transfer. ICML 2018: 5072-5081 - [c6]Yu Zhang, Ying Wei, Qiang Yang:
Learning to Multitask. NeurIPS 2018: 5776-5787 - [i3]Yu Zhang, Ying Wei, Qiang Yang:
Learning to Multitask. CoRR abs/1805.07541 (2018) - [i2]Zheng Li
Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification. CoRR abs/1811.10999 (2018) - 2017
- [c5]Zheng Li
End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification. IJCAI 2017: 2237-2243 - [c4]Bo Liu, Ying Wei
Deep Neural Networks for High Dimension, Low Sample Size Data. IJCAI 2017: 2287-2293 - [i1]Ying Wei, Yu Zhang, Qiang Yang:
Learning to Transfer. CoRR abs/1708.05629 (2017) - 2016
- [j1]Ying Wei
Heterogeneous Translated Hashing: A Scalable Solution Towards Multi-Modal Similarity Search. ACM Trans. Knowl. Discov. Data 10(4): 36:1-36:28 (2016) - [c3]Ying Wei, Yin Zhu, Cane Wing-ki Leung, Yangqiu Song, Qiang Yang:
Instilling Social to Physical: Co-Regularized Heterogeneous Transfer Learning. AAAI 2016: 1338-1344 - [c2]Ying Wei
Transfer Knowledge between Cities. KDD 2016: 1905-1914 - 2014
- [c1]Ying Wei
Scalable heterogeneous translated hashing. KDD 2014: 791-800
Coauthor Index
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last updated on 2024-11-22 19:43 CET by the dblp team
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